Bioinformatics Vol. 18 no. 8 2002
Pages 1064-1072
© 2002 Oxford University Press
A conditional density error model for the statistical analysis of microarray data
1 Aeomica, 928 East Arques Avenue, Sunnyvale, CA 94085, USA
Received on October 22, 2001
; revised on January 30, 2002
; accepted on February 15, 2002
Motivation: In many microarray experiments, relatively few intra- and inter-array replicate measurements are made due to significant cost limitations and sample availability. Compounding this problem is a lack of robust statistical methods for analyzing gene expression data with limited experimental replicates. As a result, the interpretation of the results of these experiments are difficult with little understanding of the probability of type I and type II errors.
Results: The variability in a series of replicate microarray measurements was modelled using a combination of parametric and non-parametric methods. A 3-dimensional surface was created for the conditional distribution of the variability given the mean signal intensity in both the Cy3 and Cy5 channels. The results were used as the basis for developing statistical methods for analyzing gene expression data with limited experimental replicates.
Availability: The statistical analysis scripts are available upon request.
Contact: drblove{at}yahoo.com rthomas{at}kalypsys.com
* To whom correspondence should be addressed at Informax Inc., 7600 Wisconsin Avenue, Suite 1100, Bethesda, MD 20814, USA
2 Pressent address: Kalypsys, Inc., 11099 N. Torrey Pines Road, Suite 200, La Jolla, CA 92037, USA
3 Pressent address: Amersham Biosciences, 928 East Arques Avenue, Sunnyvale, CA 94085, USA
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